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The inhibition of foliar respiration by light is a crucial yet often overlooked component in estimating ecosystem respiration. However, current estimations of the light inhibition of ecosystem respiration are biased by ignoring the effects of moisture factors. We developed a novel physics‐constrained machine learning method to quantify the extent of light inhibition (Reli) driven by multiple factors in global ecosystems. Our findings revealed significant seasonal variations in light inhibition rate aligned with vegetation growth. Temperature predominantly influenced variations in Reli, and the temperature‐Reli relationship was regulated by vapor pressure deficit rather than soil water content. A reassessment of global ecosystem respiration revealed that current Earth system models (ESMs) overestimate ecosystem respiration in mid‐to‐high latitude dryland regions, with a global average light inhibition strength of 0.51 (±0.16). Knowledge from this study provides an accurate understanding of light inhibition driven by temperature and moisture coupling in simulating carbon cycle. Plain Language Summary: Ecosystem respiration is mainly composed of vegetation respiration and soil respiration. However, estimates of ecosystem respiration are biased by ignoring the inhibition of leaf respiration in the light. We developed a novel physics‐constrained machine learning method to estimate the ecosystem respiration incorporating the ecological process of light inhibition. We found a clear relationship between light inhibition rate and vegetation growth on a seasonal scale. The light inhibition of ecosystem respiration was driven by both temperature and moisture factors. The global average light inhibition strength was 0.51 (±0.16). Key Points: Light inhibition of ecosystem respiration showed seasonal variations that match vegetation growthRelationship between temperature and light inhibition was regulated by vapor pressure deficitCurrent Earth system models overestimated ecosystem respiration in mid‐to‐high latitude dryland regions [ABSTRACT FROM AUTHOR]

Polar‐orbiting satellites have significantly improved our understanding of the terrestrial carbon cycle, yet they are not designed to observe sub‐daily dynamics that can provide unique insight into carbon cycle processes. Geostationary satellites offer remote sensing capabilities at temporal resolutions of 5‐min, or even less. This study explores the use of geostationary satellite data acquired by the Geostationary Operational Environmental Satellite—R Series (GOES‐R) to estimate terrestrial gross primary productivity (GPP) and ecosystem respiration (RECO) using machine learning. We collected and processed data from 126 AmeriFlux eddy covariance towers in the Contiguous United States synchronized with imagery from the GOES‐R Advanced Baseline Imager (ABI) from 2017 to 2022 to develop ML models and assess their performance. Tree‐based ensemble regressions showed promising performance for predicting GPP (R2 of 0.70 ± 0.11 and RMSE of 4.04 ± 1.65 μmol m−2 s−1) and RECO (R2 of 0.77 ± 0.10 and RMSE of 0.90 ± 0.49 μmol m−2 s−1) on a half‐hourly time step using GOES‐R surface products and top‐of‐atmosphere observations. Our findings align with global efforts to utilize geostationary satellites to improve carbon flux estimation and provide insight into how to estimate terrestrial carbon dioxide fluxes in near‐real time. Plain Language Summary: Fighting climate change requires an understanding of how ecosystems absorb and release carbon dioxide. While most Earth‐orbiting satellites provide limited snapshots, this study explores how more frequent imagery—every 5 min—from geostationary satellites, also known as weather satellites, can be used to estimate ecosystem carbon dioxide flux. By combining this data with machine learning techniques, we successfully estimated carbon uptake and release at over 100 US sites at half‐hourly intervals. This paves the way for near‐real‐time global monitoring of carbon exchange, offering a powerful tool for scientists and policymakers tackling climate change. Key Points: Advanced Baseline Imager (ABI) observations can estimate sub‐daily ecosystem carbon uptake and respiration at 126 AmeriFlux sitesIntegration of top‐of‐atmosphere products enhances the accuracy of monitoring land surface functionsABI observations can fill eddy covariance data gaps: up to 1 week (high accuracy), 6 months (low accuracy) [ABSTRACT FROM AUTHOR]

We measured dark CO2 fluxes and CH4 emissions from two naturally vegetated ecosystems of the Mezquital Valley irrigated with wastewater from Mexico City. The ecosystems were characterized by high groundwater levels; the vegetation was represented mainly by saltgrass in the first plot and chairmaker's bulrush in the second. A dark chamber technique was used for the study from August 2008 to June 2009. For the two studied plots, mean values (mean ± SE) for dark ecosystem CO2 fluxes (Rtot), soil CO2 emission (Rsoil), and heterotrophic respiration (Rhet) were 26 ± 5, 14 ± 3 and 12 ± 3 mg C m–2 h–1, respectively, The annual cumulative fluxes Rtot, Rsoil and Rhet equal to 234, 127 and 103 g C m–2 y–1, respectively. The contribution of Rsoil to Rtot, and Rhet to Rsoil varied significantly over the study period, with no clear relationship to seasonal dynamics. The observed low CO2 fluxes may be due to soil salinization resulting from wastewater flooding. The fluxes of CH4 were observed in the flooded plot, with peaks up to 370 µg C m–2 h–1. The fluxes of CH4 were significantly higher when plants were present in the measurement chamber than when there were no plants, confirming the important role of plant cover in CH4 transport. Unlike CH4 fluxes, CO2 fluxes show seasonal dynamics, mainly due to their strong dependence on temperature. The observed results may be useful for properly estimating the global C budget and the contribution of saline soils to C fluxes. [ABSTRACT FROM AUTHOR]

The permafrost region has accumulated organic carbon in cold and waterlogged soils over thousands of years and now contains three times as much carbon as the atmosphere. Global warming is degrading permafrost with the potential to accelerate climate change as increased microbial decomposition releases soil carbon as greenhouse gases. A 19-year time series of soil and ecosystem respiration radiocarbon from Alaska provides long-term insight into changing permafrost soil carbon dynamics in a warmer world. Nine per cent of ecosystem respiration and 23% of soil respiration observations had radiocarbon values more than 50‰ lower than the atmospheric value. Furthermore, the overall trend of ecosystem and soil respiration radiocarbon values through time decreased more than atmospheric radiocarbon values did, indicating that old carbon degradation was enhanced. Boosted regression tree analyses showed that temperature and moisture environmental variables had the largest relative influence on lower radiocarbon values. This suggested that old carbon degradation was controlled by warming/permafrost thaw and soil drying together, as waterlogged soil conditions could protect soil carbon from microbial decomposition even when thawed. Overall, changing conditions increasingly favoured the release of old carbon, which is a definitive fingerprint of an accelerating feedback to climate change as a consequence of warming and permafrost destabilization. This article is part of the Theo Murphy meeting issue 'Radiocarbon in the Anthropocene'.

Warming-induced carbon loss via ecosystem respiration (Re) is probably intensifying in the alpine grassland ecosystem of the Tibetan Plateau owing to more accelerated warming and the higher temperature sensitivity of Re (Q10). However-little is known about the patterns and controlling factors of Q10 on the plateau, impeding the comprehension of the intensity of terrestrial carbon–climate feedbacks for these sensitive and vulnerable ecosystems. Here, we synthesized and analyzed multiyear observations from 14 sites to systematically compare the spatiotemporal variations of Q10 values in diverse climate zones and ecosystems, and further explore the relationships between Q10 and environmental factors. Moreover, structural equation modeling was utilized to identify the direct and indirect factors predicting Q10 values during the annual, growing, and non-growing seasons. The results indicated that the estimated Q10 values were strongly dependent on temperature, generally, with the average Q10 during different time periods increasing with air temperature and soil temperature at different measurement depths (5 cm, 10 cm, 20 cm). The Q10 values differentiated among ecosystems and climatic zones, with warming-induced Q10 declines being stronger in colder regions than elsewhere based on spatial patterns. NDVI was the most cardinal factor in predicting annual Q10 values, significantly and positively correlated with Q10. Soil temperature (Ts) was identified as the other powerful predictor for Q10, and the negative Q10–Ts relationship demonstrates a larger terrestrial carbon loss potentiality in colder than in warmer regions in response to global warming. Note that the interpretations of the effect of soil moisture on Q10 were complicated, reflected in a significant positive relationship between Q10 and soil moisture during the growing season and a strong quadratic correlation between the two during the annual and non-growing season. These findings are conducive to improving our understanding of alpine grassland ecosystem carbon–climate feedbacks under warming climates. [ABSTRACT FROM AUTHOR]

Empirical models for estimating ecosystem respiration (ER) are widely used in CO2 flux partitioning algorithms that partition net ecosystem CO2 exchange (NEE) into gross primary productivity (GPP) and ER due to advantages of simple structures. However, empirical ER models remain limited due to single-source conceptualization that doesn’t discriminate different responses of aboveground respiration (AGR) and belowground respiration (BGR) to environmental factors (i.e., temperature and/or soil moisture). In this study, a dual-source module with only one parameter α was proposed and incorporated into six widely used ER models to enhance model capabilities. Long-term flux measurements of six typical terrestrial ecosystems and soil chamber respiration data at two sites were collected to evaluate models. Results showed that integration of the dual-source module can significantly improve the performance of empirical models in selected ecosystems with mean R2 improvement of 0.10 ± 0.16. The site years with relative increased R2 (ΔR2) larger than 10 % range from 6 % to 79 % amongst different models. Further validation between soil respiration and estimated BGR showed good correlations (r > 0.7) and demonstrated that proposed method can provide robust estimate of above/belowground respiration. Calibrated α varies amongst ecosystem types. Further analysis indicates variation of α is largely influenced by ratio of above/belowground biomass and annual average moisture conditions. Our findings highlight the critical need for partitioning ER models into dual-source for developing CO2 flux partitioning algorithms and support the approach as an effective means to enhance the understanding of global carbon cycles with changing climate.

Generally, with increasing elevation, there is a corresponding decrease in annual mean air and soil temperatures, resulting in an overall decrease in ecosystem carbon dioxide (CO2) exchange. However, there is a lack of knowledge on the variations in CO2 exchange along elevation gradients in tundra ecosystems. Aiming to quantify CO2 exchange along elevation gradients in tundra ecosystems, we measured ecosystem CO2 exchange in the peak growing season along an elevation gradient (9–387 m above sea level, m.a.s.l) in an arctic heath tundra, West Greenland. We also performed an ex-situ incubation experiment based on soil samples collected along the elevation gradient, to assess the sensitivity of soil respiration to changes in temperature and soil moisture. There was no apparent temperature gradient along the elevation gradient, with the lowest air and soil temperatures at the second lowest elevation site (83 m). The lowest elevation site exhibited the highest net ecosystem exchange (NEE), ecosystem respiration (ER) and gross ecosystem production (GEP) rates, while the other three sites generally showed intercomparable CO2 exchange rates. Topography aspect-induced soil microclimate differences rather than the elevation were the primary drivers for the soil nutrient status and ecosystem CO2 exchange. The temperature sensitivity of soil respiration above 0 °C increased with elevation, while elevation did not regulate the temperature sensitivity below 0 °C or the moisture sensitivity. Soil total nitrogen, carbon, and ammonium contents were the controls of temperature sensitivity below 0 °C. Overall, our results emphasize the significance of considering elevation and microclimate when predicting the response of CO2 balance to climate change or upscaling to regional scales, particularly during the growing season. However, outside the growing season, other factors such as soil nutrient dynamics, play a more influential role in driving ecosystem CO2 fluxes. To accurately upscale or predict annual CO2 fluxes in arctic tundra regions, it is crucial to incorporate elevation-specific microclimate conditions into ecosystem models.

Abstract The inhibition of foliar respiration by light is a crucial yet often overlooked component in estimating ecosystem respiration. However, current estimations of the light inhibition of ecosystem respiration are biased by ignoring the effects of moisture factors. We developed a novel physics‐constrained machine learning method to quantify the extent of light inhibition (Reli) driven by multiple factors in global ecosystems. Our findings revealed significant seasonal variations in light inhibition rate aligned with vegetation growth. Temperature predominantly influenced variations in Reli, and the temperature‐Reli relationship was regulated by vapor pressure deficit rather than soil water content. A reassessment of global ecosystem respiration revealed that current Earth system models (ESMs) overestimate ecosystem respiration in mid‐to‐high latitude dryland regions, with a global average light inhibition strength of 0.51 (±0.16). Knowledge from this study provides an accurate understanding of light inhibition driven by temperature and moisture coupling in simulating carbon cycle.

Abstract Polar‐orbiting satellites have significantly improved our understanding of the terrestrial carbon cycle, yet they are not designed to observe sub‐daily dynamics that can provide unique insight into carbon cycle processes. Geostationary satellites offer remote sensing capabilities at temporal resolutions of 5‐min, or even less. This study explores the use of geostationary satellite data acquired by the Geostationary Operational Environmental Satellite—R Series (GOES‐R) to estimate terrestrial gross primary productivity (GPP) and ecosystem respiration (RECO) using machine learning. We collected and processed data from 126 AmeriFlux eddy covariance towers in the Contiguous United States synchronized with imagery from the GOES‐R Advanced Baseline Imager (ABI) from 2017 to 2022 to develop ML models and assess their performance. Tree‐based ensemble regressions showed promising performance for predicting GPP (R2 of 0.70 ± 0.11 and RMSE of 4.04 ± 1.65 μmol m−2 s−1) and RECO (R2 of 0.77 ± 0.10 and RMSE of 0.90 ± 0.49 μmol m−2 s−1) on a half‐hourly time step using GOES‐R surface products and top‐of‐atmosphere observations. Our findings align with global efforts to utilize geostationary satellites to improve carbon flux estimation and provide insight into how to estimate terrestrial carbon dioxide fluxes in near‐real time.

Livestock grazing can strongly determine how grasslands function and their role in the carbon cycle. However, how ecosystem carbon exchange responds to grazing and the underlying mechanisms remain unclear. We measured ecosystem carbon fluxes to explore the changes in carbon exchange and their driving mechanisms under different grazing intensities (CK, control; HG, heavy grazing; LG, light grazing; MG, moderate grazing) based on a 16‐year long‐term grazing experimental platform in a desert steppe. We found that grazing intensity influenced aboveground biomass during the peak growing season, primarily by decreasing shrubs and semi‐shrubs and perennial forbs. Furthermore, grazing decreased net ecosystem carbon exchange by decreasing aboveground biomass, especially the functional group of shrubs and semi‐shrubs. At the same time, we found that belowground biomass and soil ammonium nitrogen were the driving factors of soil respiration in grazed systems. Our study indicates that shrubs and semi‐shrubs are important factors in regulating ecosystem carbon exchange under grazing disturbance in the desert steppe, whereas belowground biomass and soil available nitrogen are important factors regulating soil respiration under grazing disturbance in the desert steppe; this results provide deeper insights for understanding how grazing moderates the relationships between soil nutrients, plant biomass, and ecosystem CO2 exchange, which provide a theoretical basis for further grazing management. [ABSTRACT FROM AUTHOR]

Oil palm (OP) plantations have replaced large areas of forest in the tropical landscape of Southeast Asia and are major emitters of greenhouse gases (GHGs). To move towards more environmentally friendly plantation management, a hopeful approach is to implement strategies to increase vegetation complexity. These options include relaxed management of understory vegetation to increase complexity in productive plantations, passive restoration of forest areas around rivers by leaving mature oil palm during replanting, and active forest restoration along river margins with planting of forest trees. These practices have the potential to deliver a range of benefits such as soil protection, reduced erosion and sedimentation in rivers, pest control and support for biodiversity, but little is known about their impact on greenhouse gas fluxes. The aim of this study was to assess the impact of improved understory growth management and the use of riparian forestry on GHG fluxes in OP plantations, making use of two long-term experiments (the Biodiversity and Ecosystem Function in Tropical Agriculture Understory Vegetation (BEFTA UV) Project; the Riparian Ecosystem Restoration in Tropical Agriculture (RERTA) Project) in Riau Province, Sumatra, Indonesia. We measured nitrous oxide (N2O), methane (CH4) and ecosystem respiration (CO2) from mature OP sites with different levels of understory vegetation and different riparian buffer restoration treatments using the static chamber method. We used linear mixed effects models to test for treatment effects, whilst accounting for soil moisture and experimental design factors (time and space). The understory vegetation treatments (normal, reduced and enhanced complexity of understory) had no effect on N2O and CH4 flux. Regarding differences in ecosystem respiration, effects attributable to the understory vegetation treatments were not strong. For the riparian restoration treatments, the fixed effects variables in the models explained little variation in the fluxes of all GHGs. Therefore, given the proven benefits of more complex understory vegetation for supporting biodiversity and healthy ecosystem functioning, plus the potential for restored riparian buffers to support biodiversity and services and to reduce GHG emissions over time, our findings reinforce the concept that these features bring environmental benefits in OP landscapes, with no measurable effects on GHG emissions. [ABSTRACT FROM AUTHOR]

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties. [ABSTRACT FROM AUTHOR]

Increased soil nutrient availability, and associated increases in vegetation productivity, could create a negative feedback between Arctic ecosystems and the climate system, thereby reducing the contribution of Arctic ecosystems to future climate change. To predict whether this feedback will develop, it is important to understand the environmental controls over nutrient cycling in High Arctic ecosystems and their impact on carbon cycling processes. Here, we examined the environmental controls over soil nitrogen availability in a High Arctic wet sedge meadow and how abiotic factors and soil nitrogen influenced carbon dioxide exchange processes. The importance of environmental variables was consistent over the 3 years, but the magnitudes of their effect varied depending on climate conditions. Ammonium availability was higher in warmer years and wetter conditions, while drier areas within the wetland had higher nitrate availability. Carbon uptake was driven by soil moisture, active layer depth, and variability between sampling sites and years (R2 = 0.753), while ecosystem respiration was influenced by nitrogen availability, soil temperature, active layer depth, and sampling year (R2 = 0.848). Considered together, the future carbon dioxide source or sink potential of high latitude wetlands will largely depend on climate-induced changes in moisture and subsequent impacts on nutrient availability.

Improving the accuracy of monitoring cropland CO2 exchange at heterogeneous spatial scales is of high importance to limit spatial and temporal uncertainty of terrestrial carbon (C) dynamic estimates. A combination of field scale eddy covariance EC) CO2 flux data and spatially matched Sentinel-2 derived vegetation indices (VIs) was tested as an approach to upscale agricultural C flux. The ability of different VIs to estimate daily net ecosystem exchange (NEE) and gross primary productivity GPP) based on linear regression models was assessed. Most VIs showed high (>0.9) and statistically significant (p<0.001) correlations with GPP and NEE although some VIs deviated from the seasonal pattern of CO2 exchange. In contrast, correlations between ecosystem respiration (Reco) and VIs were weak and statistically not significant, and no attempt was made to estimate Reco from VIs. Linear regression models explained generally more than 80% and 70% of the variability of NEE and GPP, respectively, with high variability amongst the individual VIs. The performance in estimating daily C fluxes varied amongst VIs depending on C flux component (NEE or GPP) and observation period. RMSE values ranged from 1.35 g C m-2 d-1 using the Green Normilized Difference Vegetation Index (GNDVI) for NEE to 5 g C m-2 d-1 using the Simple Ratio SR) for GPP. This equated to an underestimated net C uptake of only 41 g C m-2 (18%) and an overestimation of gross C uptake of 854 g C m-2 (73%). Differences between measured and estimated C fluxes were mainly explained by the diversion of the C flux and VI signal during winter, when C uptake stayed low while VI values indicated an increased C uptake due to relatively high crop leaf area. Overall, results exhibited similar error margins as mechanistic crop models. Thus, they indicated suitability and developability of the proposed approach to monitor cropland C exchange with satellite derived VIs. [ABSTRACT FROM AUTHOR]

Abstract Livestock grazing can strongly determine how grasslands function and their role in the carbon cycle. However, how ecosystem carbon exchange responds to grazing and the underlying mechanisms remain unclear. We measured ecosystem carbon fluxes to explore the changes in carbon exchange and their driving mechanisms under different grazing intensities (CK, control; HG, heavy grazing; LG, light grazing; MG, moderate grazing) based on a 16‐year long‐term grazing experimental platform in a desert steppe. We found that grazing intensity influenced aboveground biomass during the peak growing season, primarily by decreasing shrubs and semi‐shrubs and perennial forbs. Furthermore, grazing decreased net ecosystem carbon exchange by decreasing aboveground biomass, especially the functional group of shrubs and semi‐shrubs. At the same time, we found that belowground biomass and soil ammonium nitrogen were the driving factors of soil respiration in grazed systems. Our study indicates that shrubs and semi‐shrubs are important factors in regulating ecosystem carbon exchange under grazing disturbance in the desert steppe, whereas belowground biomass and soil available nitrogen are important factors regulating soil respiration under grazing disturbance in the desert steppe; this results provide deeper insights for understanding how grazing moderates the relationships between soil nutrients, plant biomass, and ecosystem CO2 exchange, which provide a theoretical basis for further grazing management.

Oil palm (OP) plantations have replaced large areas of forest in the tropical landscape of Southeast Asia and are major emitters of greenhouse gases (GHGs). To move towards more environmentally friendly plantation management, a hopeful approach is to implement strategies to increase vegetation complexity. These options include relaxed management of understory vegetation to increase complexity in productive plantations, passive restoration of forest areas around rivers by leaving mature oil palm during replanting, and active forest restoration along river margins with planting of forest trees. These practices have the potential to deliver a range of benefits such as soil protection, reduced erosion and sedimentation in rivers, pest control and support for biodiversity, but little is known about their impact on greenhouse gas fluxes. The aim of this study was to assess the impact of improved understory growth management and the use of riparian forestry on GHG fluxes in OP plantations, making use of two long-term experiments (the Biodiversity and Ecosystem Function in Tropical Agriculture Understory Vegetation (BEFTA UV) Project; the Riparian Ecosystem Restoration in Tropical Agriculture (RERTA) Project) in Riau Province, Sumatra, Indonesia. We measured nitrous oxide (N2O), methane (CH4) and ecosystem respiration (CO2) from mature OP sites with different levels of understory vegetation and different riparian buffer restoration treatments using the static chamber method. We used linear mixed effects models to test for treatment effects, whilst accounting for soil moisture and experimental design factors (time and space). The understory vegetation treatments (normal, reduced and enhanced complexity of understory) had no effect on N2O and CH4 flux. Regarding differences in ecosystem respiration, effects attributable to the understory vegetation treatments were not strong. For the riparian restoration treatments, the fixed effects variables in the models explained little variation in the fluxes of all GHGs. Therefore, given the proven benefits of more complex understory vegetation for supporting biodiversity and healthy ecosystem functioning, plus the potential for restored riparian buffers to support biodiversity and services and to reduce GHG emissions over time, our findings reinforce the concept that these features bring environmental benefits in OP landscapes, with no measurable effects on GHG emissions.

Earlier snowmelt and more frequent summer drought due to climate warming are considered particularly influential for extratropical alpine plants, which are adapted to a short growing season and high water availability.Here, we explored the combined effects of the two drivers with a field experiment in late‐successional alpine grassland in the Swiss Alps (2500 m a.s.l.) over 6–7 years. We advanced and delayed snowmelt by removing and adding snow to experimental plots prior to natural snowmelt for 7 years and combined this treatment with 5 and 10 weeks of summer drought for 6 years. We measured plant biomass formation, community composition and ecosystem respiration, and monitored soil moisture as well as soil temperature.Natural snowmelt dates varied by 42 days across years. Snow manipulations advanced and delayed snowmelt by 4.6 and 8.0 days on average but did not affect annual growth (peak biomass) above‐ nor below‐ground. Interactions between snowmelt and drought were nonsignificant, implying that drought effects were independent of snowmelt.Drought reduced total annual above‐ground biomass in the 10‐week treatment by 16 ± 7% across years, while the 5‐week treatment lowered biomass in the last year only. This decline in biomass was accountable to high drought sensitivity of biomass production in a few forb and graminoid species. In contrast, drought did not affect the biomass production of the dominant sedge Carex curvula, whose proportion of total plant cover increased from 36% in controls to 48% in 10‐week drought.Below‐ground biomass slightly increased under drought (5‐week treatment only), resulting in a higher root mass fraction (both treatments). Despite continued root formation, drought reduced ecosystem respiration by 13%–23% per season, assessed nine times during three growing seasons. Since more than 85% of ecosystem respiration stemmed from below‐ground activities and roots continued growing under drought, we assume that soil microorganisms were heavily constrained by the drought treatments.Synthesis. We conclude that snowmelt timing is unrelated to productivity, while recurrent drought will shift biomass allocation from shoots to roots in this typical alpine grassland, with potential implications for grazers but also for nutrient and carbon cycling. Species‐specific drought‐sensitivity will considerably alter community composition under more frequent drought. [ABSTRACT FROM AUTHOR]

Isotopic radiocarbon (Δ14C) signatures of ecosystem respiration (Reco) can identify old soil carbon (C) loss and serve as an early indicator of permafrost destabilization in a warming climate. Warming also stimulates plant productivity causing plant respiration to dominate Reco Δ14C signatures and potentially obscuring old soil C loss. Here, we investigate how a wide spatio-temporal gradient of permafrost thaw and plant productivity affects Reco Δ14C patterns and isotopic partitioning. Spatial gradients came from a warming experiment with doubling thaw depth and variable biomass, and a vegetation removal manipulation to eliminate plant contributions. We sampled in August and September to capture transitions from high to low plant productivity, decreased surface soil temperature, and relatively small seasonal thaw extensions. We found that surface processes dominate spatial variation in old soil C loss and a process-based partitioning approach was crucial for constraining old soil C loss. Resampling the same plots in different times of the year revealed that old soil C losses tripled with cooling surface temperature, and the largest old soil C losses were detected when the organic-to-mineral soil horizons thawed (∼50–60 cm). We suggest that the measured increase in old soil respiration over the season and when the organic-to-mineral horizon thawed, may be explained by mobilization of nitrogen that stimulates microbial decomposition at depth. Our results suggest that soil C in the organic to mineral horizon may be an important source of soil C loss as the entire Arctic region warms and could lead to nonlinearities in projected permafrost climate feedbacks.

Greenhouse gases (GHGs) emissions from high-cold terrestrial ecosystems underlain by permafrost on the Qinghai–Tibet Plateau (QTP) have received widespread attention. However, the dominant factors regulating ecosystem respiration (Re) and its components (soil respiration Rs and heterotrophic respiration Rh) and how the differences in carbon emissions from different ecotypes and seasons remain are still unclear. We conducted a 2-year field investigation (August 2018 to October 2020) and applied the structural equation model (SEM) to clarify the changes in the factors controlling the respiration components during different seasons. The results indicate that the Re and its controlling factors in three alpine grassland ecosystems (alpine steppe, alpine meadow, and swamp meadow) vary with seasons. Furthermore, autotrophic respiration (Ra) contributes the most to the seasonal changes in Re. The Re gradually increases in the early growing season and rapidly decreases in the late growing season. Rh remains relatively stable during the year. Under these seasonal variations in the respiration components, the dominant factors controlling Re in the nongrowing season are the temperature of the atmosphere–soil interface (heat flux, atmospheric temperature, and soil temperature at 5 cm depth) and microbial activity (microbial carbon and pH) with the variable importance projections >1.5. During the growing season, the dominant factors regulating Re, Rs, and Rh are the soil temperature with a standardized direct effect (SDE) of 0.424, soil nutrient conditions (total nitrogen and pH) with SDEs of 0.570–0.614, and microbial activity (microbial carbon) with a SDE of 0.591, respectively. In addition, meteorological conditions have an important impact on the respiration components during the growing season. Specifically, the atmospheric vapor pressure is the dominant factor regulating the three respiration components (standardized total effects = 0.44−0.53, p

Almost half of the global terrestrial soil carbon (C) is stored in the northern circumpolar permafrost region, where air temperatures are increasing two times faster than the global average. As climate warms, permafrost thaws and soil organic matter becomes vulnerable to greater microbial decomposition. Long-term soil warming of ice-rich permafrost can result in thermokarst formation that creates variability in environmental conditions. Consequently, plant and microbial proportional contributions to ecosystem respiration may change in response to long-term soil warming. Natural abundance δ13 C and Δ14 C of aboveground and belowground plant material, and of young and old soil respiration were used to inform a mixing model to partition the contribution of each source to ecosystem respiration fluxes. We employed a hierarchical Bayesian approach that incorporated gross primary productivity and environmental drivers to constrain source contributions. We found that long-term experimental permafrost warming introduced a soil hydrology component that interacted with temperature to affect old soil C respiration. Old soil C loss was suppressed in plots with warmer deep soil temperatures because they tended to be wetter. When soil volumetric water content significantly decreased in 2018 relative to 2016 and 2017, the dominant respiration sources shifted from plant aboveground and young soil respiration to old soil respiration. The proportion of ecosystem respiration from old soil C accounted for up to 39% of ecosystem respiration and represented a 30-fold increase compared to the wet-year average. Our findings show that thermokarst formation may act to moderate microbial decomposition of old soil C when soil is highly saturated. However, when soil moisture decreases, a higher proportion of old soil C is vulnerable to decomposition and can become a large flux to the atmosphere. As permafrost systems continue to change with climate, we must understand the thresholds that may propel these systems from a C sink to a source.

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties.

The Tibet Plateau, with its extensive carbon pools, plays a pivotal role in the global carbon budget. Nevertheless, the driving factors of the carbon dioxide budget remain disputed, and the impact of freeze–thaw process on carbon release is still unclear due to the harsh climate and lack of monitoring data. To clarify the primary factors affecting the alpine meadow ecosystems and to examine the impact of freeze–thaw on carbon release, we employed the LI-8150 automated continuous measurement system. This system, in conjunction with eddy covariance meteorological data, The Boosted Regression Tree (BRT) model, and multiple stepwise regression analysis, were used to analyze the seasonal variations in carbon flux (e.g., net ecosystem carbon exchange [NEE], gross primary productivity [GPP], and ecosystem respiration [Reco]). We also investigate the carbon sources and sinks in the alpine meadow ecosystem, as well as the predominant factor of carbon flux. Our findings include: (1) the carbon sources and sinks in the alpine meadow ecosystem shift seasonally on monthly and daily scales. On a monthly scale, the ecosystem functions as a moderate carbon sink in June, July, August, and September and as a weak carbon source from October through May. (2) Overall, the alpine meadow ecosystem, located in the northeastern Qinghai Lake basin, serves as a weak carbon sink (-58.53 g C m−2 year−1). (3) Soil temperature is the primary factor driving most variations observed in NEE, Reco, and GPP, contributing 48.05 %, 78.61 %, and 65.05 %, respectively. Soil temperature, soil water dynamics influenced by freeze and thaw processes, and their interaction with plant growth collectively play a crucial role in regulating the carbon sources and sinks in ecosystems. We provide first-hand observational data for monitoring the carbon sources and sinks in the alpine meadow ecosystem of the Tibet Plateau, as well as offer future guidance for studying the carbon budget of the Tibet Plateau.

This article is a Commentary on Marshall et al. (2023), 239: 2166–2179. [ABSTRACT FROM AUTHOR]

Drought timing determines the degree to which dry events impact ecosystems, with the ability of key processes to withstand change differing between drought periods. Findings indicate that drought timing effects vary across ecosystems, with few studies focusing on alpine grasslands. We conducted a mesocosm experiment using small grassland monoliths collected in September from the high Alps and left to overwinter at 0 °C until the experiment began in lowland Italy under late-winter outdoor conditions. Together with watered controls, we imposed three different drought treatments (zero precipitation): (1) one-month early-drought immediately after simulated snowmelt; (2) one-month mid-drought a month after melt-out; and (3) continuous two-month drought across the entire experimental period. Ecosystem responses were assessed by measuring CO2 fluxes, while vegetation responses were investigated by measuring aboveground net primary production (ANPP) of graminoids and forbs and post-harvest resprouting after one-month rehydration. We found that ecosystem respiration and gross ecosystem production (GEP) during the day were more negatively affected by mid-season drought compared to drought starting early in the season. By the end of treatments, GEP reduction under mid-season drought was similar to that of a continuous two-month drought. ANPP reduction was similar in early- and mid-drought treatments, showing a greater decrease under an enforced two-month period without precipitation. Plant resprouting, however, was only reduced in full- and mid-season drought pots, with forbs more negatively affected than graminoids. Seasonal soil moisture variation can account for these patterns: remaining winter moisture allowed almost full canopy development during the first month of the season, despite precipitation being withheld, while soil moisture depletion in the second month, resulting from higher temperatures and greater biomass, caused a collapse of gas exchange and diminished plant resprouting. Our data illustrates the importance of the timing of zero-precipitation periods for both plant and ecosystem responses in alpine grasslands. [ABSTRACT FROM AUTHOR]

There is increasing interest in utilizing the high carbon sequestration capacity of wetlands as a rationale for their restoration, but this requires careful assessment of their greenhouse gas (GHG) fluxes. We used a spatially extensive sampling approach across salinity gradients and management regimes (disturbed, restored, and reference) in 22 wetland sites across two Oregon, USA estuaries, Tillamook and Coos Bays, to measure fluxes of methane (CH4), ecosystem respiration as carbon dioxide (CO2), and nitrous oxide (N2O) over 1 year and related them to environmental forcing variables. Boosted regression tree (BRT) models explained drivers of GHG fluxes reasonably well despite highly nonlinear and interactive relationships and many flux measurements below detection. We used the BRT models to predict annual GHG fluxes in a subset of restored and reference sites where continuous environmental data were recorded and compared them to previously published soil carbon sequestration rates. Most sites had net removal of CO2-equivalents from the atmosphere over both 20 and 100 year timeframes. Our results show that a spatially extensive GHG flux sampling scheme and machine-learning statistical techniques can be used to estimate GHG fluxes in other current and former wetlands within the region if environmental data are collected at a spatial resolution that reflects site variability and at sufficient duration to reflect seasonality (i.e., at least one full year). Such an approach can save time and money in determining the feasibility of wetland restoration as a climate mitigation strategy. We use our results to suggest wetland restoration strategies that optimize climate benefits. [ABSTRACT FROM AUTHOR]

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO2 between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO2 release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO2 fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co-acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data-driven approach based on combined neural networks (NNC-part ). NNC-part incorporates process knowledge by introducing a photosynthetic response based on the light-use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R2  > .94) and RECO (R2  > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NNC-part performed more realistic than the traditional methods for predicting additional patterns of gross CO2 fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO2 fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NNC-part is a valid data-driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.

Interannual variation in net ecosystem carbon production (NEP) plays an important role in the carbon cycle processes. An agricultural ecosystem may fluctuate between carbon net source and carbon sink, or it may remain neutral. Thus, the long-term trends in NEP and the relevant meteorological, soil and biotic control of interannual variation in NEP remain unclear in farmland agroecosystems. To effectively assess the carbon sequestration potential of the farmland ecosystem, the eddy covariance dataset of rain-fed spring maize in Northeast China from 2005 to 2020 are used to investigate the interannual variations in NEP and the relevant meteorological, soil and biotic influences. NEP is partitioned into gross ecosystem productivity (GEP) and ecosystem respiration (RE) to explain the interannual variations of NEP and its influencing factors. The average annual NEP, GEP and RE are 272±109, 1086±177, 820±130 g·m-2·a-1, respectively, with no significant changes. The day-to-day dynamics of NEP, GEP and RE show single peak curves. NEP and GEP reach the maximums at the very time of maize tasseling, and the maximum value of RE occurs 13 days after NEP and GEP. Compared with RE, NEP variations are mainly caused by GEP. The redundancy analysis shows the interannual variations in NEP are mainly affected by precipitation as the meteorological factor and water use efficiency as the biotic factor, and the influence weights of the meteorological and biotic factors are 28.4% and 31.4%. Meanwhile, the influence weights of the meteorological factors (photosynthetically active radiation, carbon dioxide and precipitation), soil (soil volumetric water content and soil organic carbon) and biotic factors (leaf area index and water use efficiency) are 61.0%, 43.8% and 62.8% for the interannual variations in GEP. The interannual variations in RE are mainly affected by the soil (soil volumetric water content and soil organic carbon) and the biotic factors (leaf area index), and the influence weight of the soil factors (39.3%) is larger than that of the biotic factor (29.2%). The results indicate that, under the background of climate warming, interannual variations in NEP in rain-fed spring maize agroecosystems are likely to be more sensitive to changes in moisture, while radiation and temperature will contribute to interannual NEP variations by affecting vapor pressure difference and soil water content.

Upscaling chamber measurements of soil greenhouse gas (GHG) fluxes from points to landscape scales remain challenging due to high variability of fluxes in space and time. This study measured GHG fluxes and soil parameters at selected point locations (n=268), thereby implementing a stratified sampling approach on a mixed land-use landscape (~5.8 km2). Based on these field-based measurements and remotely-sensed data on landscape and vegetation properties, we used Random Forest models to predict GHG fluxes at a landscape scale (1 m resolution) in summer and autumn. The results showed improved GHG flux prediction performance when combining field25 measured soil parameters with remotely-sensed data. Available satellite data products from Sentinel-2 on vegetation cover and water content played a more significant role than attributes derived from a digital elevation model, possibly due to their ability to capture both spatial and seasonal changes of ecosystem parameters within the landscape. Similar seasonal patterns of higher soil/ecosystem respiration (SR/ER-CO2) and nitrous oxide (N2O) fluxes in summer and higher methane (CH4) uptake in autumn were observed in both the measured and predicted landscape fluxes. Based on the upscaled fluxes, we also assessed the contribution of hot spots to total landscape fluxes. The identified emission hot spots occupied a small landscape area (7 to 16%) but accounted for up to 42% of the landscape GHG fluxes. Our study showed that combining remotely-sensed data with chamber measurements and soil properties is a promising approach for identifying spatial patterns and hot spots of GHG fluxes across heterogeneous landscapes. Such information may be used to inform targeted mitigation strategies at landscape-scale. [ABSTRACT FROM AUTHOR]

More than half of the world’s rivers experience occasional, seasonal, or permanent drying, and this may increase because of climate change. Drying, i.e. severe reduction in water flow even leading to streambed desiccation, can have a profound impact on the available aquatic habitat, biodiversity, and functions of rivers. Yet, to date, it is unclear whether similar drying events in comparable climate zones result in similar changes in ecosystem processes, such as river metabolism or greenhouse gas (GHG) emissions. Here, we synthesise the detected effects of drying on gross primary production (GPP) and ecosystem respiration (ER), as well as on the emissions of GHGs (CO _2 , CH _4 , and N _2 O) in rivers and streams. We examined the current available scientific literature detailing the impact of drying on these variables when measured either in the field or in the laboratory. We extracted data from 30 studies analysing GPP and ER responses, and data on GHG emissions from another 35 studies. Then, we conducted a meta-analysis to determine whether the magnitude and direction of the effects varied across the systems and climate zones studied, or according to the type (natural or human-induced) and severity of drying. In general, drying enhanced GPP (under low flows) and CH _4 emissions, and decreased CO _2 and N _2 O emissions. The hydrological phases throughout streambed drying (low water flow, isolated pools, or desiccation) had differential effects on metabolism and GHG emissions. The effects of drying were generally more severe when it induced desiccation, rather than just periods of low flow. Desiccation strongly reduced GPP, likely because of the die-off of algae, while its negative effect on ER was smaller. Greater decrease in GPP than in ER under desiccation would lead to increase in CO _2 emissions; our results showed accordingly that desiccation increased CO _2 emissions. Furthermore, the magnitude and direction of the effects varied depending on the study type. Experimental studies conducted in micro- and mesocosms demonstrated greater effects than field studies, thus the extrapolation of results from these to real conditions should be done with caution. Overall, the effects’ direction was inconsistent across climate zones, except for the Mediterranean climate zone, where drying was showing a negative effect on both metabolism and GHG emissions. Our synthesis may contribute to identifying the worldwide trends and patterns of drying on riverine functions associated to global change impacts on river and stream ecosystems.

The phenological cycles of terrestrial ecosystems have shifted with the changing climate, and the altered timings of biogeochemical fluxes may also exert feedback on the climate system. As regulators of land carbon balance, relative shifts in photosynthetic and respiratory phenology under climate change are of great importance. However, the relative seasonal dynamics of these individual processes and their sensitivity to climate factors as well as the implications for carbon cycling are not well understood. In this study, we examined the relationship in the seasonality of gross primary production (GPP) and ecosystem respiration (RE) as well as their temperature sensitivities and the implications for carbon uptake with around 1500 site-years’ of data from FLUXNET 2015 and Boreal Ecosystem Productivity Simulator (BEPS) at 212 sites. The results showed that RE started earlier in the spring and ended later in the autumn than GPP over most biomes. Furthermore, the flux phenology metrics responded differently to temperature: GPP phenology was more sensitive to changes during the spring temperature than RE phenology, and less sensitive to autumn temperature than RE. We found large BEPS-observation discrepancies in seasonality metrics and their apparent temperature sensitivity. The site-based BEPS projections did not capture the observed seasonal metrics and temperature sensitivities in either GPP or RE seasonality metrics. Improved understanding of the asynchrony of GPP and RE as well as different sensitivity of environmental factors are of great significance for reliable future carbon balance projections.

This study analyzed the sensitivities of carbon cycle to surface air temperature using the CO _2 flux data collected from June to September for six years (2014–2019) over a moist tundra site in Council, Alaska. The tundra ecosystem was a strong sink of carbon in June and July, a weak sink in August with rapidly decreasing photosynthesis, and a carbon source in September. The ecosystem respiration (Re) and gross primary production (GPP) were obtained from the net ecosystem exchange (NEE) of eddy-covariance system. Both the Re and GPP increased with temperature, enhancing carbon emission and uptake during observation period. Notably, Re showed higher sensitivity to temperature than GPP did. This result means that as global warming continues, the increase in carbon release is greater than the increase in carbon uptake. In other words, the tundra ecosystem is expected to become a weaker carbon sink in June and July and a stronger source of carbon in September. Possible mechanism of different temperature sensitivities of Re and GPP as well as temporal variations of temperature sensitivities are suggested. Present results highlight the importance of understanding the temperature sensitivities of Re and GPP in various tundra ecosystems to accurately understand changes in the carbon cycle in the Arctic region.

Global lakes play an active role in releasing carbon into the atmosphere. However, previous research was less focused on shallow tropical and sub-tropical lakes, especially ecosystem respiration during the drawdown period. This study was designed to determine the environmental factors that determine ecosystem respiration during the drawdown period in a typical shallow sub-tropical lake, Dongting Lake in China. Ecosystem respiration from the exposed mudflat and a newly colonized meadow were investigated using a Li-8100 soil CO2 flux system in situ. The soil water content soil organic carbon (SOC), dissolved organic carbon (DOC), total nitrogen and soil C/N ratio were measured at 0–30 cm soil depth layers. No difference was found among different soil depth layers for soil properties, while the dissolved organic carbon value varied significantly among different levels of the cumulative days of the mudflat exposed to the air (CDE). Carex colonizing significantly increased soil organic carbon and DOC at the surface soil layer. Exposure to the air and Carex colonizing together strengthened the intensity of carbon dioxide (CO2) emission in the mudflat, achieving 0.716 ± 0.114 μmol m-2s-1 and 2.240 ± 0.375 μmol m-2s-1, respectively. Exposure to the air led mudflat to exceed other landscapes or different vegetation types in Dongting Lake, becoming the most active area releasing CO2 into the atmosphere, with the respiration flux reaching a peak period at around 60 days after exposure, which was enormously reinforced by Carex colonizing. Reducing the area and duration of mudflat exposure to the air during the drawdown period might be useful in reducing CO2 emissions to the atmosphere in shallow sub-tropical lakes.

The Mukhrino field station has participated in the national project on the inventory of carbon fluxes and pools in the terrestrial ecosystems of Russia since 2022. The development of a network of measurements of CO2 fluxes and phytomass covered six types of bog ecosystems typical to Western Siberia. The gross ecosystem exchange (GEE) of the field-layer vegetation (medians for the period from the end of May to the end of July, mgC m−2 h−1; see errors in Results section) decreased in series: Sphagnum bog with sparse low pine trees ("Open bog"), ridges in ridge-hollow patterned bogs ("Ridge"), pine-dwarf shrub-Sphagnum bog ("Tall ryam"), hollows in patterned bogs ("S.hollow", "E.hollow") and pine-dwarf shrub-Sphagnum bog ("Ryam"): −220, −200, −125, −120, −109 and −86, respectively. Ecosystem respiration (Reco) here was 106, 106, 182, 55, 97 and 136. The aboveground and belowground phytomass of mosses in this series varied between 368 ± 106–472 ± 184 and 2484 ± 517–6041 ± 2079 g/m2, respectively: the aboveground phytomass of vascular plants and plant litter—15 ± 7–128 ± 95 and 10 ± 6–128 ± 43, respectively. According to the results of mathematical modeling, the best proxy for GEE, in addition to photosynthetically active radiation and soil surface temperature, was the aboveground phytomass of vascular plants (PhV), and for Reco—PhV and the mass of the plant litter of vascular plants. [ABSTRACT FROM AUTHOR]

• There was no temperature gradient along 9–387 m elevation gradient in arctic tundra. • Topography aspect-induced soil microclimate differences drove ecosystem CO 2 exchange. • Temperature sensitivity of soil respiration above 0 °C increased with elevation. • Elevation did not regulate temperature sensitivity below 0 °C or moisture sensitivity. Generally, with increasing elevation, there is a corresponding decrease in annual mean air and soil temperatures, resulting in an overall decrease in ecosystem carbon dioxide (CO 2) exchange. However, there is a lack of knowledge on the variations in CO 2 exchange along elevation gradients in tundra ecosystems. Aiming to quantify CO 2 exchange along elevation gradients in tundra ecosystems, we measured ecosystem CO 2 exchange in the peak growing season along an elevation gradient (9–387 m above sea level, m.a.s.l) in an arctic heath tundra, West Greenland. We also performed an ex-situ incubation experiment based on soil samples collected along the elevation gradient, to assess the sensitivity of soil respiration to changes in temperature and soil moisture. There was no apparent temperature gradient along the elevation gradient, with the lowest air and soil temperatures at the second lowest elevation site (83 m). The lowest elevation site exhibited the highest net ecosystem exchange (NEE), ecosystem respiration (ER) and gross ecosystem production (GEP) rates, while the other three sites generally showed intercomparable CO 2 exchange rates. Topography aspect-induced soil microclimate differences rather than the elevation were the primary drivers for the soil nutrient status and ecosystem CO 2 exchange. The temperature sensitivity of soil respiration above 0 °C increased with elevation, while elevation did not regulate the temperature sensitivity below 0 °C or the moisture sensitivity. Soil total nitrogen, carbon, and ammonium contents were the controls of temperature sensitivity below 0 °C. Overall, our results emphasize the significance of considering elevation and microclimate when predicting the response of CO 2 balance to climate change or upscaling to regional scales, particularly during the growing season. However, outside the growing season, other factors such as soil nutrient dynamics, play a more influential role in driving ecosystem CO 2 fluxes. To accurately upscale or predict annual CO 2 fluxes in arctic tundra regions, it is crucial to incorporate elevation-specific microclimate conditions into ecosystem models. [ABSTRACT FROM AUTHOR]

Abstract Background Most North American temperate forests are plantation or regrowth forests, which are actively managed. These forests are in different stages of their growth cycles and their ability to sequester atmospheric carbon is affected by extreme weather events. In this study, the impact of heat and drought events on carbon sequestration in an age-sequence (80, 45, and 17 years as of 2019) of eastern white pine (Pinus strobus L.) forests in southern Ontario, Canada was examined using eddy covariance flux measurements from 2003 to 2019. Results Over the 17-year study period, the mean annual values of net ecosystem productivity (NEP) were 180 ± 96, 538 ± 177 and 64 ± 165 g C m–2 yr–1 in the 80-, 45- and 17-year-old stands, respectively, with the highest annual carbon sequestration rate observed in the 45-year-old stand. We found that air temperature (Ta) was the dominant control on NEP in all three different-aged stands and drought, which was a limiting factor for both gross ecosystem productivity (GEP) and ecosystems respiration (RE), had a smaller impact on NEP. However, the simultaneous occurrence of heat and drought events during the early growing seasons or over the consecutive years had a significant negative impact on annual NEP in all three forests. We observed a similar trend of NEP decline in all three stands over three consecutive years that experienced extreme weather events, with 2016 being a hot and dry, 2017 being a dry, and 2018 being a hot year. The youngest stand became a net source of carbon for all three of these years and the oldest stand became a small source of carbon for the first time in 2018 since observations started in 2003. However, in 2019, all three stands reverted to annual net carbon sinks. Conclusions Our study results indicate that the timing, frequency and concurrent or consecutive occurrence of extreme weather events may have significant implications for carbon sequestration in temperate conifer forests in Eastern North America. This study is one of few globally available to provide long-term observational data on carbon exchanges in different-aged temperate plantation forests. It highlights interannual variability in carbon fluxes and enhances our understanding of the responses of these forest ecosystems to extreme weather events. Study results will help in developing climate resilient and sustainable forestry practices to offset atmospheric greenhouse gas emissions and improving simulation of carbon exchange processes in terrestrial ecosystem models.

Non-steady-state closed dynamic accumulation chambers are widely used to measure the respiration of terrestrial ecosystems, thanks to their low cost, low energy consumption and simple transportability, that allow measurements even in hostile and remote environments. However, the assessment of the accuracy and precision associated with the measurement system (independently of possible disturbances due to chamber-soil interactions) is rarely reported. This information is instead necessary for basic quality control, to compare data obtained by different devices and regression models and to provide Confidence Intervals (CIs) on the carbon flux values. This study quantifies the uncertainty associated with emission flux measurements, with a focus on very low fluxes. Calibration tests using different accumulation chambers and CO2 sensors were performed, and fluxes were calculated by means of different models (parametric, non-parametric and flux models). The results of this work show that the linear regression model has the best reproducibility when compared to the other tested models, regardless of the sensor used and the chamber volumes, while the second order polynomial regression has the best accuracy. We remark the importance of building a calibration curve in the range of the expected flux values, with an interval between the lowest and highest imposed flux that should not exceed two orders of magnitude. To evaluate the reproducibility of the measurement, performing replicates for each imposed flux value is essential. We also show that it is necessary to carefully identify the best time interval for interpolating the CO2 concentration curve in order to guarantee reproducibility and accuracy in flux estimates.

In the last few decades, temperatures in the Arctic have increased twice as much as the rest of the globe. As permafrost thaws in response to this warming, large amounts of soil organic matter may become vulnerable to decomposition. Microbial decomposition will release carbon (C) from permafrost soils, however, warmer conditions could also lead to enhanced plant growth and C uptake. Field and modeling studies show high uncertainty in soil and plant responses to climate change but there have been few studies that reconcile field and model data to understand differences and reduce uncertainty. Here, we evaluate gross primary productivity (GPP), ecosystem respiration (Reco), and net ecosystem C exchange (NEE) from eight years of experimental soil warming in moist acidic tundra against equivalent fluxes from the Community Land Model during simulations parameterized to reflect the field conditions associated with this manipulative field experiment. Over the eight-year experimental period, soil temperatures and thaw depths increased with warming in field observations and model simulations. However, the field and model results do not agree on warming effects on water table depth; warming created wetter soils in the field and drier soils in the models. In the field, initial increases in growing season GPP, Reco, and NEE to experimentally-induced permafrost thaw created a higher C sink capacity in the first years followed by a stronger C source in years six through eight. In contrast, both models predicted linear increases in GPP, Reco, and NEE with warming. The divergence of model results from field experiments reveals the role subsidence, hydrology, and nutrient cycling play in influencing the C flux responses to permafrost thaw, a complexity that the models are not structurally able to predict, and highlight challenges associated with projecting C cycle dynamics across the Arctic.

Precipitation (PPT) patterns in semiarid grasslands are characterized by infrequent and small PPT events; however, plants and soil microorganisms are adapted to use the unpredictable small pulses of water. Several studies have shown short-term responses of carbon and nitrogen mineralization rates (called the priming effect or the Birch effect) stimulated by wet-dry cycles; however, dynamics, drivers, and the contribution of the “priming effect” to the annual C balance is poorly understood. Thus, we analysed six years of continuous net ecosystem exchange measurements to evaluate the effect of the PPT periodicity, magnitude of individual PPT events on the daily/annual ecosystem C balance (NEE) in a semiarid grassland. We included the period between PPT events, a priori daytime NEE rate and a priori soil moisture content as the main drivers of the priming effect. Ecosystem respiration (ER) responded within few hours following a PPT event whereas it took five-nine days for gross ecosystem exchange (GEE; such as –NEE = GEE + ER) to respond. Precipitation events as low as 0.25 mm increased ER, but cumulative PPT > 40 mm that infiltrated deep into the soil profile stimulated GEE. Overall, ER fluxes following PPT events were related to the change of soil water content at shallow depth and previous soil conditions (e.g., previous NEE rate, previous soil water content) and the size of the stimulus (e.g., PPT event size). Carbon effluxes from priming effect accounted for less than 5% of ecosystem respiration but were significatively high respect to the carbon balance. In the long-term, changes in PPT regimes to more intense and less frequent PPT events, as expected by the climate change effect, could convert the semiarid grassland from a slight C sink to a C source. [ABSTRACT FROM AUTHOR]

Background. Agriculture is essential for food security. However, conventional agriculture alters the water and carbon cycle and soil properties. We investigated the effect of conventional management (CM) and sustainable management (SM) on the carbon and water cycle in crops of nopal (Np) and wheat (Wh). Methods. A micrometeorological eddy covariance tower was installed to measure water use through evapotranspiration (ET) and the net exchange of CO2 during the crop's development. Gross primary productivity (GPP), water use efficiency (WUE), and soil properties were obtained. Results. The results showed that both agricultural managements influenced the carbon flux of the ecosystem, with a lower GPP and Reco in the nopal field (1.85 and 0.99 mmol C m-2 s-1, respectively), compared to the wheat field (6.34 and 1.8 mmol C m-2 s-1, respectively). It was mainly attributed to the metabolic plant differences, phenological stages, and wheat biomass developed during the winter. On the other hand, the accumulated ET in the SM-Wh plots was lower than SM-Np. Therefore, the crops subjected to sustainable practices use water more efficiently with 1.42 and 1.03 g C m-3 H2O for nopal and wheat, respectively. In regard to soil properties, it was observed that tillage alters microbial activity affecting organic matter and carbon. It can be concluded that the differences in agricultural management for both crops altered the carbon and water cycle and soil quality. In addition, implementing good agricultural practices allows more efficient use of water by the plant, higher retention of water in the soil, and less ET. [ABSTRACT FROM AUTHOR]

Understanding the CO2 flux over agricultural crop fields is critical because the temporal cycle is driven by both ecological environment and anthropogenic change. We analyzed the net ecosystem exchange of CO2 measured over a barley–rice double-cropping field using the eddy covariance method for 5 years. We conducted gap-filling based on u*-threshold criteria and partitioned the net ecosystem exchange into gross primary production and respiration. The relative importance analysis of solar radiation, temperature, soil heat flux, soil water content, and vapor deficit revealed that solar radiation and temperature were the dominant contributors to net ecosystem exchange. The annual variation in the net ecosystem exchange followed a bimodal pattern driven by CO2 uptake by both barley and rice, displaying two negative peaks in late April and mid-August. The elongation stages of the crops exhibited the highest flux. Gross primary production and respiration were closely related to solar radiation and nighttime temperature, respectively. The relative importance of the other environmental variables was affected by the cultivation season and irrigation water. In the period of rice cultivation, respiration was approximately 3 µmol m−2 s−1 higher during rice drainage than during the flooded period. The accumulated net ecosystem production was estimated to be 315 gC m−2 and 349 gC m−2 for the barley and rice growing periods, respectively, and 649 gC m−2 for the annual total. These values are comparable with the results of other studies on barley–rice double-cropping fields. [ABSTRACT FROM AUTHOR]

Wetlands store large amounts of carbon stocks and are essential in both global carbon cycling and regional ecosystem services. Understanding the dynamics of wetland carbon exchange is crucial for assessing carbon budgets and predicting their future evolution. Although many studies have been conducted on the effects of climate change on the ecosystem carbon cycle, little is known regarding carbon emissions from the alpine wetlands in arid northwest China. In this study, we used an automatic chamber system (LI-8100A) to measure ecosystem respiration (ER) in the Bayinbuluk alpine wetland in northwest China. The ER showed a significant bimodal diurnal variation, with peak values appearing at 16:30 and 23:30 (Beijing time, UTC + 8). A clear seasonal pattern in ER was observed, with the highest value (19.38 µmol m−2 s−1) occurring in August and the lowest value (0.11 µmol m−2 s−1) occurring in late December. The annual ER in 2018 was 678 g C m−2 and respiration during the non-growing season accounted for 13% of the annual sum. Nonlinear regression revealed that soil temperature at 5 cm depth and soil water content (SWC) were the main factors controlling the seasonal variation in ER. The diurnal variation in ER was mainly controlled by air temperature and solar radiation. Higher temperature sensitivity (Q 10) occurred under conditions of lower soil temperatures and medium SWC (25% ≤ SWC ≤ 40%). The present study deepens our understanding of CO2 emissions in alpine wetland ecosystems and helps evaluate the carbon budget in alpine wetlands in arid regions. [ABSTRACT FROM AUTHOR]

In the terrestrial carbon cycle is very relevant to identify the influence of soil in the CO2 released to the atmosphere, which is linked to multiple biotic and abiotic drivers. Arid ecosystems dominate the trend and interannual variability of the land CO2 sink. This pattern is mainly controlled by temperature, precipitation, and shortwave radiation. Thus, these environments are characterized by a wide variability of water availability, which causes the CO2 efflux to be highly variable in time, challenging our model capacities. This study aims to understand the ecosystem CO2 fluxes and their controlling mechanisms from the Chihuahuan Desert in Northeast Mexico. We explore the average contribution of the Rsoil (1.30 mmol m-2 s‑1) to Reco (1.76 mmol m-2 s‑1), while identifying the controlling mechanisms of both on an annual scale. The structural equation model constructed showed a good fit for the data, explaining 50% and 93% of the annual variance of Rsoil and Reco, respectively. According to this model, Rsoil was mainly controlled by the air temperature, and Reco by soil water content. Unexpectedly, vapor pressure deficit was the most weight variable with a direct negative effect on Reco, supporting the idea that the vegetation component has a crucial role in the CO2 efflux of this ecosystem. This study highlights the importance of include multiple factors in the models of the C cycle.

Background Agriculture is essential for food security. However, conventional agriculture alters the water and carbon cycle and soil properties. We investigated the effect of conventional management (CM) and sustainable management (SM) on the carbon and water cycle in crops of nopal (Np) and wheat (Wh). Methods A micrometeorological eddy covariance tower was installed to measure water use through evapotranspiration (ET) and the net exchange of CO2 during the crop’s development. Gross primary productivity (GPP), water use efficiency (WUE), and soil properties were obtained. Results The results showed that both agricultural managements influenced the carbon flux of the ecosystem, with a lower GPP and Reco in the nopal field (1.85 and 0.99 mmol C m−2 s−1, respectively), compared to the wheat field (6.34 and 1.8 mmol C m−2 s−1, respectively). It was mainly attributed to the metabolic plant differences, phenological stages, and wheat biomass developed during the winter. On the other hand, the accumulated ET in the SM-Wh plots was lower than SM-Np. Therefore, the crops subjected to sustainable practices use water more efficiently with 1.42 and 1.03 g C m−3 H2O for nopal and wheat, respectively. In regard to soil properties, it was observed that tillage alters microbial activity affecting organic matter and carbon. It can be concluded that the differences in agricultural management for both crops altered the carbon and water cycle and soil quality. In addition, implementing good agricultural practices allows more efficient use of water by the plant, higher retention of water in the soil, and less ET.

The principal channel of carbon export from ecosystems to the atmosphere, and an important connection in carbon exchange between land and atmosphere, is ecosystem respiration (ER). It has a significant impact on the global carbon cycle and the rate of CO2 increase in the atmosphere. The effects of different vegetation types [Medicago sativa grassland (MS); Xanthoceras sorbifolium forestland (XS); Caragana korshinskii bushland (CK); Hippophae rhamnoides shrubland (HR); and Stipa bungeana grassland (SB)] on ecosystem respiration fluxes in Loess Hilly Region (LHR) were studied via the static chamber technique. The results showed that different vegetation types had significant effects on ER fluxes, and the decreasing order of the cumulative fluxes was HR > MS > SB > CK > XS. Throughout the study period, the largest value of ER occurred in the summer and the lowest value occurred in the winter. Temperature (air temperature, soil temperature) and soil moisture were both significantly and positively linked with ER. For the temporal change of ER, the joint effect of soil temperature and moisture was a key regulating factor. The temperature sensitivity of ecosystem respiration varies greatly between vegetation types and seasons. In the process of LHR vegetation restoration, the ER, carbon sequestration capacity and ecological benefits of different plant types should be considered in order to select the vegetation type that is most conducive to reducing the greenhouse effect.